Quantitative imaging of cerebral blood flow is essential in preclinical stroke studies for monitoring the efficacy of potential treatments and for understanding the role of vascular reorganization in functional recovery. Similarly, real-time imaging of blood flow is crucial during neurovascular surgery in humans, where intraoperative visualization of vascular patency and tissue perfusion are needed. Laser speckle contrast imaging has become widely used because it provides real-time images with very simple instrumentation and requires no exogenous contrast agents. However, laser speckle imaging is limited to imaging of relative blood flow changes within one subject, and the inability to compare flow across subjects has been a major limitation. We recently introduced an extension to speckle imaging called multi-exposure speckle imaging (MESI), that allowed chronic imaging of cerebral blood flow in mice over many weeks post-stroke. Despite this advance however comparisons across subjects remains challenging due to a lack of understanding of the physical origins of the measured signals. We know that speckle images represent a spatially integrated measure of the underlying microvascular perfusion, but the exact nature of this integration is complex and poorly understood. Exact calibration of MESI requires knowledge of the detailed scattering interactions of every detected photon with every moving particle in the tissue, as well as how each interaction contributes to the overall speckle signal. Clearly this level of detail cannot be determined experimentally. In this project we will combine a set of novel microscopy tools with a physically realistic computational model and together these new tools will allow us to establish this relationship in unprecedented detail and calibrate MESI for absolute blood flow imaging in the cortex. To do this we will create a single microscope to acquire MESI surface images along with three dimensional images of vascular structure using multiphoton fluorescence microscopy, and blood flow measurements in every vessel segment of the cortex using optical coherence tomography. This three-dimensional structural and blood flow information with be used as inputs to a computational model of MESI that will allow us to determine how each vessel segment contributes to the measured MESI signal. We will use these tools to establish absolute calibrations for MESI in mice and use the calibrations to quantify the ability of MESI to detect vascular remodeling in the cortex following stroke. Finally, we will translate MESI imaging to the clinical setting and perform a pilot study of MESI during neurovascular surgical procedures.